Resource-Aware Min-Min (RAMM) Algorithm for Resource Allocation in Cloud Computing Environment
Syed Arshad Ali1, Samiya Khan2, Mansaf Alam3
1Syed Arshad Ali, department of Computer Science, Jamia Millia Islamia, New Delhi, India.
2Samiya Khan, department of Computer Science, Jamia Millia Islamia, New Delhi, India.
3Mansaf Alam*, department of Computer Science, Jamia Millia Islamia, New Delhi, India.
Manuscript received on 5 August 2019. | Revised Manuscript received on 11 August 2019. | Manuscript published on 30 September 2019. | PP: 1863-1870 | Volume-8 Issue-3 September 2019 | Retrieval Number: C5197098319/19©BEIESP | DOI: 10.35940/ijrte.C5197.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Resource allocation (RA) is a significant aspect of Cloud Computing. The Cloud resource manager is responsible to assign available resources to the tasks for execution in an effective way that improves system performance, reduce response time, lessen makespan and utilize resources efficiently. To fulfil these objectives, an effective Tasks Scheduling algorithm is required. The standard Max-Min and Min-Min Task Scheduling algorithms are not able to produce better makespan and effective resource utilization. In this paper, a Resource-Aware Min-Min (RAMM) Algorithm is proposed based on basic Min-Min algorithm. The proposed RAMM Algorithm selects shortest execution time task and assigns it to the resource which takes shortest completion time. If minimum completion time resource is busy, then the RAMM Algorithm selects next minimum completion time resource to reduce waiting time of the task and improve resource utilization. The experiment results show that the proposed RAMM Algorithm produces better makespan and load balance than Max-Min, Min-Min and improved Max-Min Algorithms.
Keywords: Resource Allocation, Makespan, Task Scheduling, Min-Min, Max-Min.
Scope of the Article: Petroleum and Mineral Resources Engineering.